Eugene (Yoogeun) Song

I am a high-energy physicist at Imperial College London, working on neutrino physics with the Imperial High Energy Physics group on the NOvA (NuMI Off-axis \(\nu_e\) Appearance) and DUNE (Deep Underground Neutrino Experiment) collaborations, under Dr Linda Cremonesi. Both are Fermilab’s flagship American neutrino experiments — Fermilab being the United States’ national laboratory for particle physics, supported principally by the Department of Energy. On NOvA my role is a variety of physics analysis. My work sits at the point where physical modelling, machine learning and statistical inference stop being separate disciplines and start being one problem: inference under uncertainty.

That framing is also my history. I began university physics at age 7, finished a BSc at age 11, and published my first first-author paper in MNRAS Letters at age 19. Since then I have worked across general relativity and early-universe cosmology, black hole magnetospheres and Blandford–Znajek energy extraction, GRMHD modelling of Sgr A*, physics-informed neural networks for clinical electrophysiology, and, at present, neutrinos and beyond-Standard-Model physics. The range looks scattered from the outside. From the inside it is one method applied to different data.

Four things occupy me at the moment. First, systematics-aware ML reconstruction for the DUNE Near Detector — the ND is not merely a control detector; it is the constraint engine that makes precision oscillation measurements possible. Second, AtriPINN: physics-informed neural networks that map atrial fibrillation from grid electrograms in real time, at ~78 ms end-to-end latency and ~1.6 mm RMS localisation error. Third, a part-time quantum computing collaboration with Singularity Quantum — quantum-accelerated computational fluid dynamics for non-invasive cardiovascular diagnostics, where I work with their CFD engineers on augmenting and enhancing the CFD model, and on the hybrid layer around it: the physics-informed machinery that infers the boundary conditions, conditions what gets handed to the quantum kernel, and puts a calibrated uncertainty on the number a cardiologist actually acts on. Fourth, quantitative research — from October 2025 to August 2026 I ran an independent practice on alpha under non-stationary market dynamics, treated as a physics problem in signal and noise rather than a curve-fitting exercise. That work is now folded back into the same question the rest of my research asks.

I care about building things that are reproducible, scalable, and principled, and I would rather re-examine a premise than optimise inside someone else’s. If you are working on hard problems in neutrinos, in machine learning for physics, in quantum computing, or in markets, I would like to hear from you.

More about me

From being celebrated as a prodigy for my academic achievements in my teens to conducting cutting-edge research in Physics at Imperial College London, my journey presents a relentless drive to push the boundaries of science and technology.

Early recognition positioned me to inspire others. Today, as a Physics graduate researcher at Imperial, I am leveraging my multidisciplinary expertise in particle physics and machine learning to drive impactful global scientific advancements. In 2026 I work at the intersection of physics, ML and bioengineering; from October, for my PhD, I move to neutrino oscillations and interactions. For now I want to continue living in Europe and to make it home here.

Outside physics I have built end-to-end quant capability: time-series and stochastic control (HJB), with a focus on production constraints — Monte Carlo, high-performance optimisation, and robust monitoring. I build long-horizon, robust, durable systems: reproducible, scalable, and principled. My strength is first-principles mastery across physics, mathematics, and quantitative finance. I am also open to the possibility of leading global STEM innovation in industry, where science evolves into real-world applications.

The early record. In October 2005, at the age of 7, I set a national record by enrolling in the Physics BSc programme at Inha University, with coursework commencing in February 2006. Soon after, I transitioned to a Computer Science programme at the National Institute for Lifelong Education (NILE). In 2009, at the age of 11, I earned my Bachelor’s through NILE’s Academic Credit Bank System — a record that remains unmatched.

Graduate work in Korea. In 2009, I joined the integrative (Master’s + PhD) programme at the Korea University of Science and Technology (UST) and the Korea Astronomy and Space Science Institute (KASI). Whilst there I authored four papers in cosmology and high-energy astrophysics, two of them published in Monthly Notices of the Royal Astronomical Society and The Astrophysical Journal. I completed the PhD coursework there, finished with All-But-Dissertation status, and left UST in August 2018.

Since then. From December 2018 to August 2020 I completed my mandatory national service, which was essential for my personal growth. Since 2023 I have been living in the UK — 2023–2024 at UCL, and from 2024 studying and working as a graduate researcher in the Department of Physics at Imperial, ranked #2 globally in the QS World University Rankings for three years in a row, from 2025 to 2027.

Where to find me. LinkedIn is where I am most active, with Bluesky next.